To determine whether a biopsychosocial model of suicidality, specifically sleep, nutrition, physical exercise, mindfulness, social connectedness, lower socioeconomic status (SES) and sex are uniquely associated with increased suicidal ideation, longitudinally over adolescence.

Longitudinal, prospective cohort study.

A structured self-report questionnaire was collected as part of the Longitudinal Adolescent Brain Study at the University of the Sunshine Coast’s Thompson Institute (Queensland, Australia) from July 2018 to January 2024.

159 Australian adolescents (n=91 female; 68 male) aged 12 to 17 years.

Self-reported suicidal ideation was measured longitudinally. Data were also collected on self-reported lifestyle factors (sleep, nutrition, physical exercise, mindfulness and social connectedness), psychological distress, SES and sex. All measures were collected at 4-monthly intervals for each participant for up to 5 years (maximum of 15 time points).

Significant relationships were identified between increased suicidal ideation and poor sleep (OR 2.6, 95% CI 1.4 to 4.6, p=0.002), socioeconomic disadvantage (SES quintile 1: OR 6.3, 95% CI, 1.8 to 21.8, p=0.004; SES quintile 2: OR 8.7, 95% CI 1.4 to 56.2, p=0.022), psychological distress (OR 5.7, 95% CI 2.1 to 15.6, p≤0.001) and eating habits (β –0.08, 95% CI –0.2 to –0.0).

Poor sleep, socioeconomic disadvantage, psychological distress and eating habits were all found to be significantly associated with increased adolescent suicidal ideation over time. These biopsychosocial factors should be considered in targeted interventions and policies for reducing adolescent suicidality. Further research should employ multilevel modelling to examine factor interactions and rigorously evaluate interventions targeting lifestyle factors and socioeconomic inequalities through randomised controlled trials and quasi-experimental designs.

This study aimed to (1) assess Lumos data quality, a New South Wales (NSW) statewide linked health data asset; and (2) determine sociodemographic variation in health service utilisation of general practice, emergency department and admitted services.

A retrospective cohort study using Lumos, a linked health data asset.

A representative statewide sample population of NSW, Australia.

People residing within NSW with an electronic health record at a Lumos participating general practice between January 2010 and June 2023.

Data quality indicators of Lumos including completeness, representativeness against NSW population data, consistency and timeliness. Furthermore, variation in general practice visits, emergency department presentations and hospital admission rates stratified by age, sex, rurality and Index of Relative Socio-economic Disadvantage (IRSD)—a measure of socioeconomic status used in Australia, where lower values represent greater relative disadvantage across a range of metrics such as education and income.

At the time of analysis, Lumos included records from 5.2 million unique patients, representing half (49.7%) of the NSW resident population. Limiting data to 2022, the Lumos population distribution broadly aligned with the 2021 Census except for IRSD quintile four and five which were under-represented (15.0% vs 20.4% (standardised difference –0.14)), and over-represented (29.7% vs 19.9% (standardised difference 0.23)), respectively. Age and greater relative disadvantage were associated with higher rates of general practice visits and hospital admissions. Greater relative disadvantage was also associated with higher rates of emergency department presentations.

Lumos’s ability to overcome historical limitations of separately managed health data in Australia and its demonstrated data quality present an opportunity to enhance health system policy and planning in NSW. The variation in service utilisation across primary and tertiary care by population and geography apparent in Lumos reinforces the need for tailored service planning.